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Extend MCP

Create a splitter

create_splitter

Create a saved, reusable splitter (split group). Start from config (inline split classifications — call get_documentation with https://docs.extend.ai/splitting/configuration.md before hand-authoring one) or cloneSplitterId (copy another splitter's draft config) — mutually exclusive; name alone creates an empty draft. The draft is the only mutable surface — edit it with update_splitter, freeze it with publish_splitter_version, run it with split_document.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesDisplay name for the splitter.
configNoInline split config: { splitClassifications: [{ id, type, description, identifierKey? }], splitRules?, advancedOptions?, parseConfig? }. Must include a type: "other" entry; ids must be unique. identifierKey names a per-segment value the splitter reads off each segment (e.g. an invoice number), surfaced as identifier on each returned split. Before authoring a config by hand, call get_documentation with https://docs.extend.ai/splitting/configuration.md and follow it.
environmentYes"TEST" = the Test (development) environment, "PRODUCTION" = live. Must match a granted target from get_me (an API key pins one environment).
workspaceIdYesTarget workspace (ws_...). Must be a granted workspace — get_me lists the accepted values.
cloneSplitterIdNoExisting splitter (spl_...) whose draft config to copy.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
nameYes
createdAtNo
updatedAtNo
draftVersionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already signal mutation (readOnlyHint=false) and non-idempotency, and the description adds meaningful behavioral context: the result is a saved, reusable draft; the draft is the only mutable surface; and the creation modes have mutually exclusive semantics. This goes beyond what annotations alone convey, though it does not describe response details—which is acceptable given an output schema exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three dense sentences carry all essential information with no filler. The core purpose is front-loaded, and each sentence adds a distinct layer: what is created, how to start, and what happens next in the lifecycle.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 5-parameter tool with nested objects and an output schema, the description covers the creation workflow, parameter relationships, documentation prerequisite, and downstream lifecycle. Combined with the fully described schema, nothing needed to invoke it correctly seems missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds relationship semantics not present in the schema: config and cloneSplitterId are mutually exclusive and name alone creates an empty draft. It also restates the critical config constraint (must include a type: "other" entry) in prose, reinforcing the schema without fully duplicating it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Create a saved, reusable splitter (split group)', which clearly distinguishes it from sibling creation tools like create_classifier or create_extractor. The lifecycle references to update_splitter, publish_splitter_version, and split_document further anchor its unique role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly explains the two starting modes (config vs cloneSplitterId) and that they are mutually exclusive, plus the fallback of name-only creating an empty draft. It also directs the agent to call get_documentation before hand-authoring config and names the exact downstream tools for editing, publishing, and running the splitter.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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